Academic literature on the topic 'Padrão IEEE 802.16'

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Journal articles on the topic "Padrão IEEE 802.16"

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Bodson, Dennis. "ITU maintains IEEE 802, 16 wirelessman standard recommendations [Standards]." IEEE Vehicular Technology Magazine 3, no. 2 (June 2008): 19–38. http://dx.doi.org/10.1109/mvt.2008.923970.

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Shrivastava, Smriti, and Md Abdullah. "A Survey: IEEE 802. 16 Wireless MAN (Wi-Max) using Various Modulation Techniques." International Journal of Computer Applications 92, no. 14 (April 18, 2014): 27–33. http://dx.doi.org/10.5120/16078-5305.

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Manikandan, R., and K. Selvakumar. "An Improved Analysis of MAC IEEE 802. 16 in Wireless Ad hoc Networks." International Journal of Computer Applications 55, no. 8 (October 20, 2012): 23–27. http://dx.doi.org/10.5120/8775-2713.

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VeerSingh, Shiv, Rajeev Paulus, A. K. Jaiswal, and Anil Kumar. "To Evaluate the Performance of IEEE 802. 16 Routing Protocols using Qualnet 6. 1 Simulator." International Journal of Computer Applications 92, no. 3 (April 18, 2014): 10–13. http://dx.doi.org/10.5120/15988-4940.

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Kaur, Avinash, Harvinder Singh, and Parveen Sharma. "Bandwidth Allocation Scheduling Algorithms for IEEE 802. 16 WiMax Protocol to Improve QoS: A Survey." International Journal of Computer Applications 98, no. 11 (July 18, 2014): 16–22. http://dx.doi.org/10.5120/17227-7550.

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Kumar, Hitesh. "Performance Analysis of LTE and IEEE 802. 16 WiMAX in terms of Attenuation and BER via MATLAB; Scenario based ROF Amalgamation as Backhaul Technology." International Journal of Computer Applications 97, no. 20 (July 18, 2014): 32–36. http://dx.doi.org/10.5120/17127-7787.

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Trang, Pham Thi Quynh, Bui Manh Thang, and Dang Thanh Hai. "Single Concatenated Input is Better than Indenpendent Multiple-input for CNNs to Predict Chemical-induced Disease Relation from Literature." VNU Journal of Science: Computer Science and Communication Engineering 36, no. 1 (May 30, 2020). http://dx.doi.org/10.25073/2588-1086/vnucsce.237.

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Chemical compounds (drugs) and diseases are among top searched keywords on the PubMed database of biomedical literature by biomedical researchers all over the world (according to a study in 2009). Working with PubMed is essential for researchers to get insights into drugs’ side effects (chemical-induced disease relations (CDR), which is essential for drug safety and toxicity. It is, however, a catastrophic burden for them as PubMed is a huge database of unstructured texts, growing steadily very fast (~28 millions scientific articles currently, approximately two deposited per minute). As a result, biomedical text mining has been empirically demonstrated its great implications in biomedical research communities. Biomedical text has its own distinct challenging properties, attracting much attetion from natural language processing communities. A large-scale study recently in 2018 showed that incorporating information into indenpendent multiple-input layers outperforms concatenating them into a single input layer (for biLSTM), producing better performance when compared to state-of-the-art CDR classifying models. This paper demonstrates that for a CNN it is vice-versa, in which concatenation is better for CDR classification. To this end, we develop a CNN based model with multiple input concatenated for CDR classification. Experimental results on the benchmark dataset demonstrate its outperformance over other recent state-of-the-art CDR classification models. Keywords: Chemical disease relation prediction, Convolutional neural network, Biomedical text mining References [1] Paul SM, S. Mytelka, C.T. Dunwiddie, C.C. Persinger, B.H. Munos, S.R. Lindborg, A.L. Schacht, How to improve R&D productivity: The pharmaceutical industry's grand challenge, Nat Rev Drug Discov. 9(3) (2010) 203-14. https://doi.org/10.1038/nrd3078. [2] J.A. DiMasi, New drug development in the United States from 1963 to 1999, Clinical pharmacology and therapeutics 69 (2001) 286-296. https://doi.org/10.1067/mcp.2001.115132. [3] C.P. Adams, V. Van Brantner, Estimating the cost of new drug development: Is it really $802 million? Health Affairs 25 (2006) 420-428. https://doi.org/10.1377/hlthaff.25.2.420. [4] R.I. Doğan, G.C. Murray, A. Névéol et al., "Understanding PubMed user search behavior through log analysis", Oxford Database, 2009. [5] G.K. Savova, J.J. Masanz, P.V. Ogren et al., "Mayo clinical text analysis and knowledge extraction system (cTAKES): Architecture, component evaluation and applications", Journal of the American Medical Informatics Association, 2010. [6] T.C. Wiegers, A.P. Davis, C.J. Mattingly, Collaborative biocuration-text mining development task for document prioritization for curation, Database 22 (2012) pp. bas037. [7] N. Kang, B. Singh, C. Bui et al., "Knowledge-based extraction of adverse drug events from biomedical text", BMC Bioinformatics 15, 2014. [8] A. Névéol, R.L. Doğan, Z. Lu, "Semi-automatic semantic annotation of PubMed queries: A study on quality, Efficiency, Satisfaction", Journal of Biomedical Informatics 44, 2011. [9] L. Hirschman, G.A. Burns, M. Krallinger, C. Arighi, K.B. Cohen et al., Text mining for the biocuration workflow, Database Apr 18, 2012, pp. bas020. [10] Wei et al., "Overview of the BioCreative V Chemical Disease Relation (CDR) Task", Proceedings of the Fifth BioCreative Challenge Evaluation Workshop, 2015. [11] P. Verga, E. Strubell, A. McCallum, Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction, In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies 1 (2018) 872-884. [12] Y. Shen, X. Huang, Attention-based convolutional neural network for semantic relation extraction, In: Proceedings of COLING 2016, the Twenty-sixth International Conference on Computational Linguistics: Technical Papers, The COLING 2016 Organizing Committee, Osaka, Japan, 2016, pp. 2526-2536. [13] Y. Peng, Z. Lu, Deep learning for extracting protein-protein interactions from biomedical literature, In: Proceedings of the BioNLP 2017 Workshop, Association for Computational Linguistics, Vancouver, Canada, 2016, pp. 29-38. [14] S. Liu, F. Shen, R. Komandur Elayavilli, Y. Wang, M. Rastegar-Mojarad, V. Chaudhary, H. Liu, Extracting chemical-protein relations using attention-based neural networks, Database, 2018. [15] H. Zhou, H. Deng, L. Chen, Y. Yang, C. Jia, D. Huang, Exploiting syntactic and semantics information for chemical-disease relation extraction, Database, 2016, pp. baw048. [16] S. Liu, B. Tang, Q. Chen et al., Drug–drug interaction extraction via convolutional neural networks, Comput, Math, Methods Med, Vol (2016) 1-8. https://doi.org/10.1155/2016/6918381. [17] L. Wang, Z. Cao, G. De Meloet al., Relation classification via multi-level attention CNNs, In: Proceedings of the Fifty-fourth Annual Meeting of the Association for Computational Linguistics 1 (2016) 1298-1307. https://doi.org/10.18653/v1/P16-1123. [18] J. Gu, F. Sun, L. Qian et al., Chemical-induced disease relation extraction via convolutional neural network, Database (2017) 1-12. https://doi.org/10.1093/database/bax024. [19] H.Q. Le, D.C. Can, S.T. Vu, T.H. Dang, M.T. Pilehvar, N. Collier, Large-scale Exploration of Neural Relation Classification Architectures, In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018, pp. 2266-2277. [20] Y. LeCun, L. Bottou, Y. Bengio, P. Haffner, Gradient-based learning applied to document recognition, In Proceedings of the IEEE. 86(11) (1998) 2278-2324. [21] Y. Kim, Convolutional neural networks for sentence classification, ArXiv preprint arXiv:1408.5882. [22] C. Nagesh, Panyam, Karin Verspoor, Trevor Cohn and Kotagiri Ramamohanarao, Exploiting graph kernels for high performance biomedical relation extraction, Journal of biomedical semantics 9(1) (2018) 7. [23] H. Zhou, H. Deng, L. Chen, Y. Yang, C. Jia, D. Huang, Exploiting syntactic and semantics information for chemical-disease relation extraction, Database, 2016.
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Dissertations / Theses on the topic "Padrão IEEE 802.16"

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Gakhar, Kamal. "Ingénierie de la QoS sur une plaque radio mixte IEEE 802. 16/ IEEE 802. 11e." Télécom Bretagne, 2007. http://www.theses.fr/2007TELB0048.

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La thèse porte sur l'ingénierie de la Qualité de Service sur un réseau radio mixant les technologies IEEE 802. 16 et IEEE 802. 11. Le projet IROISE, qui suscite cette étude, définit une architecture dans laquelle des points d'accès sont reliés à un Point de Présence (POP) d'opérateur par une BLR ~= 40Ghz, et les points d'accès 802. 11 sont accessibles à des usagers fixes, ou peu mobiles (marche à pied). L'argument du projet est d'étudier comment supporter des services nécessitant soit une bande passante garantie, soit de la QoS (en matière de délai ou de gigue) sur une telle architecture. La thèse portera sur la spécification des mécanismes à mettre en oeuvre dans les équipements de la plaque IROISE afin de supporter ces services. Ces équipements sont essentiellement les serveurs localisés au niveau du POP et les équipements couplant technologies IEEE 802. 16 et IEEE 802. 11.
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Yin, Fei. "Evaluation et optimisation de performance dans les réseaux IEEE 802. 16." Paris 6, 2009. http://www.theses.fr/2009PA066123.

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IEEE 802. 16 définit un mécanisme d’allocation de la bande passante basé sur réservation. Dans ce mécanisme, sont définis les deux principaux modes de polling : le polling mode unicast et le polling mode contention. Il faudrait avoir un mécanisme pour adopter les deux modes de polling afin d’optimiser la performance. Nous proposons un simple mais efficace mécanisme de polling pour adopter les deux modes de polling d’une manière efficiente et équitable, qui optimise enfin la performance. Le mode contention est utilisé par les applications comme nrtPS et BE pour demander la bande passante à lien montant. Le nombre de la bande passante alloué aux requêtes sur contention va influencer d’une façon significative la performance. Nous analysons et développons un simple modèle mathématique pour évaluer la performance. Une période optimale contention-request dans cette trame est introduite. La taille optimale est aussi influencée par le nombre des terminaux dans le réseau, ceci est aussi analysé
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Ghazal, Sahar. "Quality of service management model for point to multi point architecture in IEEE 802. 16 (WiMAX)." Versailles-St Quentin en Yvelines, 2010. http://www.theses.fr/2010VERS0009.

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Le standard IEEE 802. 16 est une véritable révolution dans les réseaux métropolitains sans fil (WirelessMANs). Il permet d'échanger à haut-débit des données, de la vidéo et de la voix. La dénomination commerciale donnée à la version 802. 16-2004 est WiMAX (Worldwide Interoperability for Microwave Access). Le standard ou supporte le mode point à multi-point (PMP) ainsi que Mesh (maillé). Dans le mode PMP, plusieurs stations clientes (SS, subscriber station) sont connectées à une station de base (BS). Le canal descendant (DL, downlink) permet à une SS de recevoir une donnée en provenance d'une BS, le canal montant (UL, uplink) permettant l'échange en sens inverse. WiMAX intègre la qualité de service (QoS) principalement par différentiation de cinq classes de trafic: unsolicited grant service (UGS), real-time polling service (rtPS), extended realtime polling service (ertPS), non-real-time polling service (nrtPS) et best effort (BE). L'architecture de la QoS est définie dans la couche MAC qui différencie les trafics associés aux classes précédentes et ordonnance la voie montante pour la classe UGS. Les grands défis de recherche dans ce domaine sont : 1) comment partager la bande passante entre les différentes stations clientes en tenant compte de la QoS demandée et 2) comment supporter plus d'utilisateurs sans impacter la QoS globale ? Cette thèse se concentre sur ces deux questions. Nous avons surtout contribué au contrôle d'admission, à la gestion de trafic et à l'ordonnancement UL/DL. Nous proposons une nouvelle architecture de QoS distribuée, où la station cliente prends une part importante dans le contrôle de la QoS à travers la classification, le modelage de trafic et l'ordonnancement. Un modèle analytique basé sur les chaînes de Markov est utilisé pour analyser la performance du contrôle d'accès (AC), où différentes priorités sont attribuées aux classes de trafic. A partir de ce modèle a été conçu un algorithme auto configurable d'AC fondé sur la logique floue. Pour contrôler le taux d'utilisation du réseau, un gestionnaire de trafic est mis en place côté client (SS) pour chaque classe de trafic (multi-gestionnaire). Et pour partager les ressources équitablement, nous avons implémenté un ordonnanceur temps-réel adaptatif (RTAS) utilisant l'ordonnancement Deficit Round Robin
IEEE 802. 16 standard is a real revolution in wireless metropolitan area networks (WirelessMANs) that enables high-speed access to data, video, and voice services. Worldwide Interoperability for Microwave Access (WiMAX) is the industry name given to the 802. 16-2004 amendment. The standard supports point-to-multipoint (PMP) as well as mesh mode. In the PMP mode, multiple subscriber stations (SSs) are connected to one base station (BS). The access channel from the BS to the SS is called the downlink (DL) channel, and the one from the SS to the BS is called the uplink (UL) channel. WiMAX is designed to provide inbuilt quality of service (QoS) mainly through the differentiation of five types of traffic flows: unsolicited grant service (UGS), real-time polling service (rtPS), extended realtime polling service (ertPS), non-real-time polling service (nrtPS) and best effort (BE). QoS architecture is defined in the MAC layer that supports classification for the pre mentioned classes and uplink scheduling for only UGS class. The great challenge of research activities in this domain is 1) how to share the bandwidth between the different stations (SS) according to the needed QoS and 2) how to increase the number of users without decreasing the overall QoS? The objective of this thesis is focused on these two points. Our contributions are essentially in admission control, traffic policing, and UL/DL scheduling. A new distributed QoS architecture is proposed, where the SS takes an important part in controlling the QoS through classification, traffic shaping and scheduling. An analytical model based on Markov chains is used to analyse the performance of the AC , where different priorities are assigned between the different traffic classes. This analytical study leads to the design of a self-configuring AC algorithm based on fuzzy logic. To control traffic rate in the network, a traffic policer is implemented in the SS side for each traffic class (multi-policer). And to share the available resources fairly, a real-time adaptive scheduler (RTAS) based on deficit round robin concept is constructed
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SILVA, M. M. O. "Uma proposta de abordagem fuzzy para tratamento de QoS em redes IEEE 802.16." Universidade Federal do Espírito Santo, 2008. http://repositorio.ufes.br/handle/10/4085.

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Made available in DSpace on 2016-08-29T15:32:32Z (GMT). No. of bitstreams: 1 tese_2833_DissertacaoMestradoMaxMauroOliveiraSilva.pdf: 3763196 bytes, checksum: 2d85717ef3309d7be2262f6947e6f494 (MD5) Previous issue date: 2008-11-04
O padrão IEEE 802.16 foi desenvolvido no intuito de padronizar as redes metropolitanas de acesso sem fio de banda larga. Ele introduz diversas vantagens, incluindo mecanismos de suporte a QoS na camada MAC. Para garantir qualidade de serviço a diferentes tipos de aplicações é preciso definir um algoritmo para distribuir de forma eficiente recursos entre as conexões. Considerando a natureza dinâmica e imprevisível das redes convergentes atuais, este trabalho propõe uma nova abordagem para distribuir recursos no canal downlink em redes 802.16. Como uma alternativa µas soluções analíticas tradicionais, a proposta apresentada baseia-se em lógica fuzzy. Comparada µa modelagem analítica, a abordagem fuzzy proporciona maior flexibilidade e generalidade às soluções devido à sua baixa especificidade e por permitir a inclusão de decisões ad-hoc.
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Carsenat, David. "Contribution à l'étude de réseaux de communication sans fil : Application au LMDS." Limoges, 2003. http://aurore.unilim.fr/theses/nxfile/default/7e8e22b4-5d30-4813-8e3d-0367b844e76b/blobholder:0/2003LIMO0039.pdf.

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Ce mémoire est consacré à l'étude de réseaux de communication sans fils haut débit fonctionnant dans la bande de fréquence 40 Ghz. Nous nous intéressons principalement aux réseaux de type LMDS (Local Multipoint Distribution System) puisque ce rapport s'inscrit dans le cadre d'un projet RNRT (Réseau national de recherche en télécommunications) appelé ERASME. Ce projet vise à étudier les performances d'un système LMDS basé sur la norme DVB (Digital Video Broadcasting). La couche MAC (Medium Access Control) utilisée dans la plateforme ERASME est étudiée dans le détail à l'aide d'un logiciel spécifique nommé OPNET qui permet la mise au point d'un outil de dimensionnement de réseaux sans fils. Aux vues des performances de la norme DVB lorsqu'elle est soumise à des applications multimédia comme la visioconférence, ce mémoire présente et étudie la norme IEEE 802. 16 qui se révèle être beaucoup plus flexible que le standard DVB
This document is dedicated to the study of high speed wireless communication networks functioning in the 40 GHz frequency band. We will be mainly interested in the LMDS (Local Multipoint Distribution System) networks since this report has been written within the framework of an RNRT project (Réseau national de recherche en télécommunications) called ERASME. This project aims at studying the performances of an LMDS system based on the DVB (Digital Video Broadcasting) standard. The MAC layer (Medium Access Control) used in the ERASME platform is studied in detail witn an application software named OPNET which allows the development of a tool for dimensioning wireless networks. Because of the DVB standard performances submitted to multimedia applications like the videconference, this document presents and studies the IEEE 802. 16 standard which proves to be much more flexible than DVB standard
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Books on the topic "Padrão IEEE 802.16"

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Yang, Xiao, and Yi Pan. Emerging Wireless LANs, Wireless PANs, and Wireless MANs: IEEE 802. 11, IEEE 802. 15, 802. 16 Wireless Standard Family. Wiley & Sons, Incorporated, John, 2009.

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Kamali, Behnam. AeroMACS: An IEEE 802. 16 Standard-Based Technology for the Next Generation of Air Transportation Systems. IEEE, 2018.

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Conference papers on the topic "Padrão IEEE 802.16"

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Ghaffarian, Hossein, Mahmood Fathy, and Mohsen Soryani. "Channel access delay analysis of IEEE 802-16 Best Effort services." In IEEE INFOCOM 2008 - IEEE Conference on Computer Communications Workshops. IEEE, 2008. http://dx.doi.org/10.1109/infocom.2008.4544597.

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